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@rich-iannone rich-iannone released this 10 Sep 22:22
· 1 commit to main since this release
v0.7.0
f3846e9

Greenwood v0.7.0 pushes the Greenwood library well beyond classical Cox regression into machine learning, cure models, interval-censored data, and additive hazards. This release adds four families of survival ML estimators (RandomSurvivalForest, ExtraSurvivalTrees, SurvivalTree, and GradientBoostingSurvivalAnalysis), the Turnbull NPMLE for interval-censored outcomes, MixtureCure and AalenAdditive regression models, the BuckleyJames semiparametric AFT estimator, the IPCW-based IPCRidge, and the maxcombo_test weighted log-rank procedure for non-proportional hazards. Diagnostics get a big boost too: Weibull probability plots, Schoenfeld residual plots, AFT residual diagnostics, thresholded-Weibull MPS fitting, and Altair-based predicted-survival visualizations. The tidy/glance layer now covers AalenJohansen, MultiState, NelsonAalen, RoystonParmar, and CoxNet, and the user guide gains new chapters on machine learning, mixture cure models, additive hazards, and interval censoring.

New Features

  • Random Survival Forest, Extra Trees, and Survival Trees — Log-rank splitting tree ensembles (RandomSurvivalForest, ExtraSurvivalTrees, SurvivalTree) with an optional Numba-accelerated split kernel for large datasets. (#40)
  • Gradient Boosting Survival Analysis — Cox-loss gradient boosting with squared-error regression tree base learners, plus variable_importance for feature ranking. (#40)
  • Altair predicted-survival plots — New Altair-based visualization for predicted survival curves from ML estimators. (#40)
  • IPCRidge estimator — Ridge-regularized accelerated failure time regression using inverse-probability-of-censoring weights, with the underlying IPCW utilities exposed for reuse. (#41)
  • Aalen additive hazards model — New AalenAdditive estimator for time-varying additive hazard regression, including a predict() method for cumulative regression coefficients. (#42)
  • Mixture cure model — MixtureCure with EM estimation for populations containing a cured fraction, validated against R's smcure. (#43)
  • Weibull diagnostic plots — New Weibull probability plotting utility for graphical assessment of Weibull AFT model fit. (#44)
  • AFT residual diagnostics — Comprehensive AFT residual types (Cox-Snell, martingale, deviance, standardized) with a log-density derivative helper backing them. (#45)
  • Turnbull interval-censored estimator — Self-consistent NPMLE Turnbull estimator for left-, right-, and interval-censored data, with RMST and RMRL support. (#46)
  • Thresholded Weibull AFT (MPS) — Maximum product-of-spacings fitting for three-parameter thresholded Weibull models, with matching visualization support. (#47)
  • Buckley-James AFT estimator — New BuckleyJames rank-based semiparametric AFT regression, complementing the parametric AFT family.
  • MaxCombo weighted log-rank test — New maxcombo_test procedure combining multiple Fleming-Harrington weights (early, mid, late, proportional) to detect survival differences under non-proportional hazards.
  • Schoenfeld residual plots — New diagnostic visualization for assessing the proportional-hazards assumption in Cox models.
  • Proportional-odds Royston-Parmar scale — RoystonParmar now supports a proportional-odds parameterization alongside the existing proportional-hazards scale.

Enhancements

  • Tidy/glance adapters added for AalenJohansen, MultiState, NelsonAalen, RoystonParmar, and CoxNet, extending broom-compatible summaries across nearly all estimators.
  • KaplanMeier.quantile() for computing median and arbitrary survival quantiles with confidence intervals.
  • FineGray.to_frame() for tabular output of Fine-Gray subdistribution hazards fits.
  • Cox influence-plotting utilities for identifying influential observations.
  • Expanded test coverage across forest estimators, Royston-Parmar, penalized Cox, GT-based risk tables, viz modules (Schoenfeld, forest plot, smoothed HR, predicted survival), and tidy/glance regressions.
  • New R-parity fixtures for Aalen additive hazards, IPCRidge, MaxCombo, cure models, Turnbull–KM equivalence, and thresholded Weibull, with all existing fixtures refreshed.

Documentation

  • New machine-learning chapter covering RSF, ExtraTrees, and gradient boosting.
  • New mixture cure model chapter in the user guide.
  • New Aalen additive hazards documentation.
  • New Buckley-James regression documentation.
  • New Turnbull interval-censoring section, plus expanded Kaplan-Meier guide coverage.
  • New MaxCombo non-proportional-hazards test documentation.
  • New Weibull diagnostic plot section in the visualization guide.
  • New parametric AFT residuals section in the Cox diagnostics guide.
  • Expanded CoxNet guidance in the Cox regression chapter.
  • Expanded AIC/BIC model-selection and summary documentation.
  • Cox influence-plotting docs added to the diagnostics guide.
  • Survival glossary expanded with modeling terms, AFT residual types, survival transforms, and ensemble concepts.

Maintenance

  • New parity CI job runs the heavy R-parity extras separately from the main test matrix.
  • Added numba as an optional dev dependency for the accelerated tree split kernel.
  • Datasets expanded with e1684 (used for cure-model validation).
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